Resource partitioning between two young‐of‐year cownose rays <i>Rhinoptera bonasus</i> and <i>R. brasiliensis</i> within a communal nursery inferred by trophic biomarkers
Bibliographic record
Abstract
Although interspecific trophic interactions plays a principal role within elasmobranch communal nurseries, little is known over variation in foraging strategies adopted by young‐of‐year of sympatric species. To test the hypothesis of dietary resource partitioning between batoids within a communal nursery, we investigated two cownose ray species, Rhinoptera bonasus and R. brasiliensis, which occur in heterospecific groups, a strategy predicted to increase survival and foraging success. Using two biochemical tracers, fatty acids (FA) and stable isotopes (δ15N and δ13C), the combined effects of maternal investment and the formation of heterospecific groups implying competition for, or partitioning of available food resources were investigated. Through univariate and multivariate analyses of biochemical tracers in several tissues (fin clip, muscle, liver, red blood cells; RBC) and plasma, our results revealed significant interspecific differences in tracers between the two species. Total FAs (∑saturated FA, ∑monounsaturated FA and ∑polyunsaturated FA) and trophic biomarkers (i.e., docosahexaenoic acid, arachidonic acid, oleic acid and δ15N) were the principle tracers responsible for the differences detected. These data revealed that R. brasiliensis was less enriched in physiologically important essential FAs than R. bonasus. Our findings suggest that these congeneric species differ in maternal investment strategy and moderately partition food resources over relatively fine spatial scales within a single nursery habitat to limit competition. These results provide further knowledge on the foraging strategies adopted by batoids in communal nursery areas, information that is required for improving spatial conservation and management planning.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".